Stimulus continuity is not necessary for the salience of dynamic sound localization cues.
Bibliographic record
Abstract
Correspondence between head rotation and resulting changes in interaural difference cues provides information about sound source location. We assessed whether source continuity or merely relative displacement is necessary for use of this dynamic localization cue. Low-frequency (0.5–1 kHz) noise-band targets, not correctly localizable in the absence of head motion or for motion duration <50 ms [Macpherson and Kerr, APCAM (2008)], were presented while the listener performed a practiced head rotation at 50 deg/s. The stimuli were either continuous (a single burst gated on and off as the head entered and exited a variable-width spatial window) or discrete (two 20 ms endpoint bursts, triggered as the head entered and exited the window). Human listeners reported the apparent location of the stimulus by orienting with their heads subsequent to the initial head rotation. The minimum head movement angle (MHMA) necessary to resolve front/rear ambiguity was measured for each stimulus type. Similar MHMAs of 5–10 deg were measured for continuous and discrete stimuli, suggesting that endpoint “snapshots'' providing only displacement information are sufficient for use of dynamic localization cues. That parallels the finding that stimulus continuity does not improve detection of source motion [Chandler and Grantham, J. Acoust. Soc. Am. 106, 1956–1968 (1992)]. [Work supported by NSF and NIH/NIDCD.]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".